Dynamics of drug resistance-associated mutations in HIV-1 DNA reverse transcriptase sequence during effective ART.

Objectives: To investigate the dynamics of HIV-1 variants archived in cells harbouring drug resistance-associated mutations (DRAMs) to lamivudine/emtricitabine, etravirine and rilpivirine in patients under effective ART free from selective pressure on these DRAMs, in order to assess the possibility of recycling molecules with resistance history. Patients and methods: We studied 25 patients with at least one DRAM to lamivudine/emtricitabine, etravirine and/or rilpivirine identified on an RNA sequence in their history and with virological control for at least 5 years under a regimen excluding all drugs from the resistant class. Longitudinal ultra-deep sequencing (UDS) and Sanger sequencing of the reverse transcriptase region were performed on cell-associated HIV-1 DNA samples taken over the 5 years of follow-up. Results: Viral variants harbouring the analysed DRAMs were no longer detected by UDS over the 5 years in 72% of patients, with viruses susceptible to the molecules of interest found after 5 years in 80% of patients with UDS and in 88% of patients with Sanger. Residual viraemia with <50 copies/mL was detected in 52% of patients. The median HIV DNA level remained stable (2.4 at baseline versus 2.1 log10 copies/106 cells 5 years later). Conclusions: These results show a clear trend towards clearance of archived DRAMs to reverse transcriptase inhibitors in cell-associated HIV-1 DNA after a long period of virological control, free from therapeutic selective pressure on these DRAMs, reflecting probable residual replication in some reservoirs of the fittest viruses and leading to persistent evolution of the archived HIV-1 DNA resistance profile.

Performance of genotypic algorithms for predicting tropism for HIV-1 CRF01_AE recombinant.

OBJECTIVES: There is no consensus about the performances of genotypic rules for predicting HIV-1 non-B subtype tropism. Three genotypic methods were compared for CRF01_AE HIV-1 tropism determination. METHODS: The V3 env region of 207 HIV-1 CRF01_AE and 178 B subtypes from 17 centers in France and 1 center in Switzerland was sequenced. Tropism was determined by Geno2Pheno algorithm with false positive rate (FPR) 5% or 10%, the 11/25 rule or the combined criteria of the 11/25, net charge rule and NXT/S mutations. RESULTS: Overall, 72.5%, 59.4%, 86.0%, 90.8% of the 207 HIV-1 CRF01_AE were R5-tropic viruses determined by Geno2pheno FPR5%, Geno2pheno FPR10%, the combined criteria and the 11/25 rule, respectively. A concordance of 82.6% was observed between Geno2pheno FPR5% and the combined criteria for CRF01_AE. The results were nearly similar for the comparison between Geno2pheno FPR5% and the 11/25 rule. More mismatches were observed when Geno2pheno was used with the FPR10%. Neither HIV viral load, nor current or nadir CD4 was associated with the discordance rate between the different algorithms. CONCLUSION: Geno2pheno predicted more X4-tropic viruses for this set of CRF01_AE sequences than the combined criteria or the 11/25 rule alone. For a conservative approach, Geno2pheno FPR5% seems to be a good compromise to predict CRF01_AE tropism.

Disparities in HIV-1 transmitted drug resistance detected by ultradeep sequencing between men who have sex with men and heterosexual populations.

OBJECTIVES: Transmitted drug resistance (TDR) can impair the response to first-line antiretroviral therapy. In treatment-naïve patients chronically infected with HIV type 1 (HIV-1), it was previously shown through Sanger sequencing that TDR was more common in men who have sex with men (MSM) than in other transmission risk groups. We aimed to compare two HIV-1 transmission groups in terms of the presence of TDR mutations. METHODS: We investigated, through Sanger sequencing and ultradeep sequencing (UDS), the presence of resistance mutations, both in majority (> 20%) and in minority (1-20%) proportions, in 70 treatment-naïve MSM and 70 treatment-naïve heterosexual patients who recently screened positive for HIV-1. RESULTS: The global prevalence of TDR was not significantly different between the two groups, either by Sanger or by UDS. Nevertheless, a higher frequency of nucleoside reverse transcriptase inhibitor TDR was observed among heterosexual patients (P = 0.04). There was also a trend for a higher frequency of TDR among MSM infected with HIV-1 subtype B compared with MSM infected with HIV-1 non-B subtypes (P = 0.06). CONCLUSIONS: Ultradeep sequencing UDS allowed sensitive monitoring of TDR, and highlighted some disparities between transmission groups.

Usefulness of an HIV DNA resistance genotypic test in patients who are candidates for a switch to the rilpivirine/emtricitabine/tenofovir disoproxil fumarate combination.

OBJECTIVES: In the context of a rilpivirine/emtricitabine/tenofovir disoproxil fumarate switch in HIV-1-infected patients with at least 1 year of virological success, we determined whether proviral DNA is an alternative to plasma HIV RNA for resistance genotyping. METHODS: Resistance-associated mutations (RAMs) in DNA after at least 1 year of virological success [viral load (VL) <50 copies/mL] were compared with those identified in the last plasma RNA genotype available. Rilpivirine/emtricitabine/tenofovir disoproxil fumarate RAMs studied were K65R, L100I, K101E/P, E138A/G/K/R/Q, V179L, Y181C/I/V, M184V/I, Y188L, H221Y, F227C and M230I/L in the RT. We studied patients without virological failure (VF) and with at least 1 VF (two consecutive VLs >50 copies/mL). Kappa's coefficient was used to measure agreement between the DNA and RNA genotypes. RESULTS: In patients without VF (n = 130) and with VF (n = 114), RNA and DNA showed resistance to at least one drug of the rilpivirine/emtricitabine/tenofovir disoproxil fumarate combination in 8% and 9% and in 60% and 45%, respectively. For rilpivirine RAMs, correlation between RNA and DNA was higher in patients without VF than in patients with VF (kappa = 0.60 versus 0.19, P = 0.026). Overall, the prevalence of RAMs was lower in DNA than in RNA. CONCLUSIONS: Incomplete information provided by the DNA genotypic test is more notable in patients with VF, suggesting that all resistance mutations associated with prior VF have not been archived in the proviral DNA or decreased to a level below the threshold of detection. In the case where no historical plasma genotypic test is available, DNA testing might be useful to rule out switching to rilpivirine/emtricitabine/tenofovir disoproxil fumarate.

Performance of genotypic algorithms for predicting tropism of HIV-1CRF02_AG subtype.

BACKGROUND: Several genotypic rules for predicting HIV-1 non-B subtypes tropism are commonly used, but there is no consensus about their performances. OBJECTIVES: Three genotypic methods were compared for CRF02_AG HIV-1 tropism determination. STUDY DESIGN: V3 env region of 178HIV-1 CRF02_AG from Pitié-Salpêtrière and Saint-Antoine Hospitals was sequenced from plasma HIV-1 RNA. HIV-1 tropism was determined by Geno2Pheno algorithm, false positive rate (FPR) 5% or 10%, the 11/25 rule or the combined criteria of the 11/25 and net charge rule. RESULTS: A concordance of 91.6% was observed between Geno2pheno 5% and the combined criteria. The results were nearly similar for the comparison between Geno2pheno 5% and the 11/25 rule. More mismatches were observed when Geno2pheno was used with the FPR 10%. A lower nadir CD4 cell count was associated with a discordance of tropism prediction between Geno2pheno 5% and the combined criteria or the 11/25 rule (p=0.02 and p=0.03, respectively). A lower HIV-1 viral load was associated with some discordance for the comparison of Geno2pheno 10% and the combined rule (p=0.02). CONCLUSION: Geno2pheno FPR 5% or 10% predicted more X4-tropic viruses for this set of CRF02_AG sequences than the combined criteria or the 11/25 rule alone. Furthermore, Geno2pheno FPR 5% was more concordant with the 11/25 rule and the combined rule than Geno2pheno 10% to predict HIV-1 tropism. Overall, Geno2pheno 5% could be used to predict CRF02_AG tropism as well as other genotypic rules.